Estimating equations for measures of association between repeated binary responses
Estimating equations for measures of association between repeated binary responses
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DOI：
10.2307/2533051
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发表时间：
1996-09-01
期刊：
影响因子：
1.9
通讯作者：
Fitamaurice, GM
中科院分区：
文献类型：
--
作者：
Lipsitz, SR;Fitamaurice, GM
许多作者提出了基于矩的方法，使用边际比值比作为关联度量来分析重复的二元响应。 Carey、Zeger 和 Diggle (1993, Biometrika 80, 517-526) 最近描述了如何使用基于条件残差（关于条件期望的偏差）的广义估计方程 (GEE) 来估计边际优势比。在本文中，我们表明，二元响应对之间关联的其他度量（例如相关性）也可以使用条件残差来估计。我们证明，与最大似然或二阶估计方程（GEE2）相比，基于条件残差的相关性估计几乎是有效的，除非相关性很大。与基于无条件残差的常用 GEE 估计器相比，该估计器还可以产生更有效的相关性估计。此外，当某些响应缺失或不完整时，或者当簇大小不相等时（在簇数据设置中），效率的提高可能相当可观。
Moment-based methods for analyzing repeated binary responses using the marginal odds ratio as a measure of association have been proposed by a number of authors. Carey, Zeger, and Diggle (1993, Biometrika 80, 517-526) have recently described how the marginal odds ratio can be estimated using generalized estimating equations (GEE) based on conditional residuals (deviations about conditional expectations). In this paper, we show that other measures of association between pairs of binary responses, e.g., the correlation, can also be estimated using conditional residuals. We demonstrate that the estimator of the correlation based on conditional residuals is nearly efficient when compared with maximum likelihood or second order estimating equations (GEE2) except when the correlation is large. This estimator also yields more efficient estimates of the correlation than the usual GEE estimator that is based on unconditional residuals. Furthermore, the gains in efficiency can be quite considerable when some of the responses are missing or incomplete, or, alternatively, when cluster sizes are unequal (in the clustered data setting).